1. Field of the Invention
The present invention relates generally to the field of communications, and more specifically, to the field of coded speech communications.
2. Description of Related Art
During a conversation between two or more people, ambient background noise is typically inherent to the overall listening experience of the human ear. FIG. 1 illustrates the analog sound waves 100 of a typical recorded conversation that includes ambient background noise signal 102 along with speech groups 104-108 caused by voice communication. Within the technical field of transmitting, receiving, and storing speech communications, several different techniques exist for coding and decoding a signal 100. One of the techniques for coding and decoding a signal 100 is to use an analysis-by-synthesis coding system, which is well known to those skilled in the art.
FIG. 2 illustrates a general overview block diagram of a prior art analysis-by-synthesis system 200 for coding and decoding speech. An analysis-by-synthesis system 200 for coding and decoding signal 100 of FIG. 1 utilizes an analysis unit 204 along with a corresponding synthesis unit 222. The analysis unit 204 represents an analysis-by-synthesis type of speech coder, such as a code excited linear prediction (CELP) coder. A code excited linear prediction coder is one way of coding signal 100 at a medium or low bit rate in order to meet the constraints of communication networks and storage capacities. An example of a CELP based speech coder is the recently adopted International Telecommunication Union (ITU) G.729 standard, herein incorporated by reference.
In order to code speech, the microphone 206 of the analysis unit 204 receives the analog sound waves 100 of FIG. 1 as an input signal. The microphone 206 outputs the received analog sound waves 100 to the analog to digital (A/D) sampler circuit 208. The analog to digital sampler 208 converts the analog sound waves 100 into a sampled digital speech signal (sampled over discrete time periods) which is output to the linear prediction coefficients (LPC) extractor 210 and the pitch extractor 212 in order to retrieve the formant structure (or the spectral envelope) and the harmonic structure of the speech signal, respectively.
The formant structure corresponds to short-term correlation and the harmonic structure corresponds to long-term correlation. The short-term correlation can be described by time varying filters whose coefficients are the obtained linear prediction coefficients (LPC). The long-term correlation can also be described by time varying filters whose coefficients are obtained from the pitch extractor. Filtering the incoming speech signal with the LPC filter removes the short-term correlation and generates a LPC residual signal. This LPC residual signal is further processed by the pitch filter in order to remove the remaining long-term correlation. The obtained signal is the total residual signal. If this residual signal is passed through the inverse pitch and LPC filters (also called synthesis filters), the original speech signal is retrieved or synthesized. In the context of speech coding, this residual signal has to be quantized (coded) in order to reduce the bit rate. The quantized residual signal is called the excitation signal, which is passed through both the quantized pitch and LPC synthesis filters in order to produce a close replica of the original speech signal. In the context of analysis-by-synthesis CELP coding of speech, the quantized residual is obtained from a code book 214 normally called the fixed code book. This method is
The fixed code book 214 of FIG. 2 contains a specific number of stored digital patterns, which are referred to as code vectors. The fixed code book 214 is normally searched in order to provide the best representative code vector to the residual signal in some perceptual fashion as known to those skilled in the art. The selected code vector is typically called the fixed excitation signal. After determining the best code vector that represents the residual signal, the fixed code book unit 214 also computes the gain factor of the fixed excitation signal. The next step is to pass the fixed excitation signal through the pitch synthesis filter. This is normally implemented using the adaptive code book search approach in order to determine the optimum pitch gain and lag in a "closed-loop" fashion as known to those skilled in the art. The "closed-loop" method, or analysis-by-synthesis, means that the signals to be matched are filtered. The optimum pitch gain and lag enable the generation of a so-called adaptive excitation signal. The determined gain factors for both the adaptive and fixed code book excitations are then quantized in a "closed-loop" fashion by the gain quantizer 216 using a look-up table with an index, which is a well known quantization scheme to those of ordinary skill in the art. The index of the best fixed excitation from the fixed code book 214 along with the indices of the quantized gains, pitch lag and LPC coefficients are then passed to the storage/transmitter unit 218.
The storage/transmitter 218 (of FIG. 2) of the analysis unit 204 then transmits to the synthesis unit 222, via the communication network 220, the index values of the pitch lag, pitch gain, linear prediction coefficients, the fixed excitation code vector, and the fixed excitation code vector gain which all represent the received analog sound waves signal 100. The synthesis unit 222 decodes the different parameters that it receives from the storage/transmitter 218 to obtain a synthesized speech signal. To enable people to hear the synthesized speech signal, the synthesis unit 222 outputs the synthesized speech signal to a speaker 224.
The analysis-by-synthesis system 200 described above with reference to FIG. 2 has been successfully employed to realize high quality speech coders. As can be appreciated by those skilled in the art, natural speech can be coded at very low bit rates with high quality. The high quality coding at a low-bit rate can be achieved by using a fixed excitation code book 214 whose code vectors have high sparsity (i.e., with few non-zero elements). For example, there are only four non-zero pulses per 5 ms in the ITU Recommendation G.729. However, when the speech is noise-like such as unvoiced speech or is corrupted by ambient background noise, the perceived performance of these coding systems is degraded. This degradation can be remedied only if the fixed code book 214 contains high-density non-zero pseudo-random code vectors and if the waveform-matching criterion in CELP systems is relaxed.
Sophisticated solutions including multi-mode coding and the use of mixed excitations have been proposed to improve the speech quality of noise-like speech such as unvoiced speech or speech under background noise conditions. However, these solutions usually lead to undesirably high complexity or high sensitivity to transmission errors. The present invention provides a simple solution to combat this problem.